A conceptual alternative forecasting model for alternative investments


In this article we present a conceptual model for forecasting purposes that can be used from fund managers or investors. Our conceptual model is a hybrid model and borrows concepts from machine learning; more specifically, from artificial neural networks (ANN) and fuzzy logic (FL). We propose the use of the nonlinear autoregressive network with exogenous inputs (NARX) which is a recurrent dynamic network, with feedback connections enclosing several layers of the network. This ANN is combined with a FL component to deal with uncertainties when considering various market conditions. The proposed conceptual forecasting model has an open architecture design so as to be extended and optimized based on investors’ needs.

Publication DOI: https://doi.org/10.5750/jpm.v12i2.1541
Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
College of Business and Social Sciences > Aston Business School
Publication ISSN: 1750-676X
Last Modified: 08 Dec 2023 11:10
Date Deposited: 08 Jul 2019 09:43
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Related URLs: http://ubplj.or ... ticle/view/1541 (Publisher URL)
PURE Output Type: Article
Published Date: 2018-06-30
Accepted Date: 2018-06-22
Authors: Stafylas, Dimitrios (ORCID Profile 0000-0002-0326-1877)
Mari, Konstantina



Version: Accepted Version

Access Restriction: Restricted to Repository staff only

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